Many therapeutic drugs have been withdrawn from market because they were found to cause Torsade de Pointes (TdP), a rare cardiac arrhythmia that often results in death. Because TdP is associated with prolongation of the QT interval (long QT) on electrocardiograms, new drugs must now be tested for their effect on long QT before they can be approved. Thus, assays to predict QT prolongation have become increasingly important to the pharmaceutical industry. Current assays are performed in vitro or in cell culture and are limited by biological simplicity, low throughput, a high rate of false positives, and an inability to detect drug-drug interactions. In vivo assays in mammals are expensive and time-consuming. A great need exists for an in vivo assay that can rapidly and accurately predict QT prolongation in humans. A recent study showed that compounds that cause long QT in humans cause bradycardia in live zebrafish embryos. In Phase I, we propose to refine this assay to more accurately predict which compounds will cause long QT in humans, develop algorithms for automation of the assay to increase throughput, and to further develop the assay for detecting drug-drug interactions caused by inhibition of Cytochrome P450 3A, the enzyme responsible for most known drug-drug interactions in humans. In phase II, full automation of the assay will be implemented and the assay will eventually be provided as a commercial service to pharmaceutical companies.